Key takeaways: Why using the “Spotify Model” of team design is not enough The four fundamental team topologies needed for modern software delivery The three team interaction modes that enable fast flow and rapid learning How to address Conway’s Law, cognitive load, and team evolution with Team Topologies For effective, modern, cloud-connected software systems we need to organize our teams in certain ways. Taking account of Conway’s Law, we look to match the team structures to the required software architecture, enabling or restricting communication and collaboration for the best outcomes. This talk will cover the basics of organization design using Team Topologies, exploring a selection of key team types and how and when to use them in order to make the development and operation of your software systems as effective as possible. The talk is based on the forthcoming 2019 book Team Topologies and first-hand experience helping companies around the world with the design of their technology teams. About Team Topologies Team Topologies is a clear, easy-to-follow approach to modern software delivery with an emphasis on optimizing team interactions for flow. Four fundamental types of team – team topologies – and three core team interaction modes combine with awareness of Conway’s Law, team cognitive load, and responsive organization evolution to define a no-nonsense, team-friendly, humanistic approach to building and running software systems. Devised by experienced IT consultants Matthew Skelton and Manuel Pais, the Team Topologies approach is informed by the well-known DevOps Team Topologies patterns (also authored and curated by Matthew and Manuel). Matthew and Manuel have worked with many organizations around the world to help them shape their teams for modern software delivery, and Team Topologies is the result of that experience. teamtopologies.com

1. TeamTopologies.com
@TeamTopologies
Beyond the Spotify model
using Team Topologies for
fast flow and organisation evolution
Matthew Skelton, Conflux
co-author of Team Topologies - @matthewpskelton
DevTest North, Leeds - 25 Sept 2019

2. TeamTopologies.com
@TeamTopologies
Welcome
DevTest North 2019

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The Spotify Model
Limitations
Team Topologies
Getting started

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6. The Spotify model of
team design for
software delivery
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Henrik Kniberg & Anders Ivarsson, 2012
https://blog.crisp.se/wp-content/uploads/2012/11/SpotifyScaling.pdf

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The Spotify model
Squad: semi-autonomous delivery team
Tribe: family of Squads - related work
Chapter: line management within a Tribe
Guild: cross-Tribe interest/specialist group

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The Spotify model has
been hugely helpful to
100s of organizations

10. The Spotify model
helps to...
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Encourage flow
of change

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Establish and
clarify team
responsibilities

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Promote good
kinds of team
collaboration

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Plan and budget
for cross-team
enablers

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The Spotify model helps to
Encourage flow of change
Establish and clarify team responsibilities
Promote good kinds of team collaboration
Plan and budget for cross-team enablers
@matthewpskelton / @TeamTopologies

16. Limitations of the
Spotify model
16

17. “This article is only a snapshot of our
current way of working - a journey in
progress, not a journey completed. By
the time you read this, things have
already changed.”
- Kniberg & Ivarsson
17

18. There is No Spotify Model
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Marcin Floryan, 2016
https://www.infoq.com/presentations/spotify-culture-stc

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Software sizing
and cognitive
load

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Heuristics for
Conway’s Law

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Patterns for
team
interactions

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Triggers for
change and
evolution

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We also need to address
Software sizing and cognitive load
Heuristics for Conway’s Law
Patterns for team interactions
Triggers for change and evolution
@matthewpskelton / @TeamTopologies

24. Team Topologies
24

25. topology
the way in which constituent parts are
interrelated or arranged
Greek: τοπολογία (τόπος == ‘place’)
25

26. Team Topologies
26
Research over 5 years across multiple industry sectors
Informed by 50+ peer-reviewed journal articles
30+ client organizations - consulting and training since
2013 with orgs in CN, EU, IN, US, UK, +
Book: 12+ case studies from well-known organizations

27. Origins - DevOps Topologies
27
CC BY-SA devopstopologies.com
@matthewpskelton / @TeamTopologies

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Philip Fisher-Ogden,
Director of Engineering at
Netflix:
“thanks for your insightful
articulations of devops
topologies. They inspired
many discussions and
helped us to think about
what model Netflix teams
could be/are using.”
https://twitter.com/philip_pfo/status/999074792123740160

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Crystal Hirschorn,
Director of Engineering at
Condé Nast International
“Your topological models
resonated extremely well
on both the Dev and Ops
side btw! I like the balanced
arguments, e.g. different
perspectives, for each
pattern.”
https://twitter.com/cfhirschorn/status/1103387659890819073

30. Team Topologies
30
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
Publication date: Sept 2019
IT Revolution Press
Pre-order from Amazon:
https://teamtopologies.com/book

31. 💥#1 on Amazon
Business and Organizational Learning
31

32. “innovative tools and concepts for
structuring the next generation
digital operating model”
Charles T. Betz, Principal Analyst, Forrester Research
32

33. Team Topologies for fast flow
Conway’s Law
Team-first
Thinking
Team
Interactions
Sensing for
Evolution
33

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Software sizing
and cognitive
load

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Team-first Thinking

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Team-first Thinking
The team is the means of delivery

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Team-first Thinking
Design for team cognitive load

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Team-first Thinking
Choose boundaries for team ownership

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Team-first Thinking
Physical and digital workspace

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Team-first Thinking
The team is the means of delivery
Design for team cognitive load
Choose boundaries for team ownership
Physical and digital workspace
@matthewpskelton / @TeamTopologies

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Heuristics for
Conway’s Law

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Conway’s Law

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Conway’s Law
Heuristic for ‘natural’ expected design

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Conway’s Law
Mirroring in tech system + human system

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Conway’s Law
Reverse Conway to mitigate worst effects

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Conway’s Law
Constraint on solution search space

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Conway’s Law
Heuristic for ‘natural’ expected design
Mirroring in tech system + human system
Reverse Conway to mitigate worst effects
Constraint on solution search space
@matthewpskelton / @TeamTopologies

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Patterns for
team
interactions

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Team Interactions

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Team Interactions
3 defined Interaction Modes

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Team Interactions
Collaboration: 2 teams working together

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Team Interactions
X-as-a-Service: 1 provides, 1 consumes

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Team Interactions
Facilitating: 1 team helps another

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Team Interactions
3 defined Interaction Modes
Collaboration: 2 teams working together
X-as-a-Service: 1 provides, 1 consumes
Facilitating: 1 team helps another
@matthewpskelton / @TeamTopologies

55. 4 fundamental topologies
55
Stream-aligned team
Enabling team
Complicated Subsystem team
Platform team

56. 4 fundamental topologies
56
Flow of change

57. 3 core interaction modes
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Flow of change
X-as-a-Service
Facilitating
Collaboration

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Triggers for
change and
evolution

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Sensing for Evolution

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Sensing for Evolution
Not all teams in the org look the same

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Sensing for Evolution
Discover, then push to Platform

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Sensing for Evolution
Awkward team interactions are signals

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Sensing for Evolution
Evolve the org with changing ecosystem

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Sensing for Evolution
Not all teams in the org look the same
Discover, then push to Platform
Awkward team interactions are signals
Evolve the org with changing ecosystem
@matthewpskelton / @TeamTopologies

65. Getting started with
the Team Topologies
approach
65

66. Getting started
66
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

67. How well can the team as a unit “grok”
the systems they own and develop?
Push some things into a Platform?
Are skills or capabilities missing?
Explicit cognitive load
67

68. Getting started
68
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

69. Are there major mismatches between
the team interactions and the required
software / system architecture?
What could be easily adjusted?
Large Conway mismatches
69

70. Getting started
70
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

71. What would change if we adopted the
3 team interaction patterns?
Collaboration, X-as-a-Service, Facilitating
How would teams react & behave?
Team Interactions
71

72. Getting started
72
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

73. How is your Platform defined?
What is the thinnest platform that
could work?
What’s needed to run an support it?
Thinnest Viable Platform
73

74. Getting started
74
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

75. Review
75

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The Spotify model helps to
Encourage flow of change
Establish and clarify team responsibilities
Promote good kinds of team collaboration
Plan and budget for cross-team enablers
@matthewpskelton / @TeamTopologies

77. 77
We also need to address
Software sizing and cognitive load
Heuristics for Conway’s Law
Patterns for team interactions
Triggers for change and evolution
@matthewpskelton / @TeamTopologies

78. Team Topologies for fast flow
Conway’s Law
Team-first
Thinking
Team
Interactions
Sensing for
Evolution
78

79. Getting started
79
Explicit cognitive load
Large Conway mismatches
Team Interactions
Thinnest Viable Platform

80. Team Topologies
80
Organizing business and
technology teams for fast flow
Matthew Skelton & Manuel Pais
Publication date: Sept 2019
IT Revolution Press
Pre-order from Amazon.com:
https://teamtopologies.com/book

81. Training
81
Day 1
Fundamentals
Day 2
Deep Dive
Day 3
Applying in Context
teamtopologies.com/training

82. Team Topologies
Fundamentals
26 Sept 2019, Leeds, UK
Details: teamtopologies.com
run by: hosted by:
with Matthew Skelton
1-day training course
Photo:JaxDevOps

83. 15% discount:
FRIEND15
TeamTopologies.com
83

84. Sign up for news and tips:
TeamTopologies.com
84

85. Thank you!
teamtopologies.com
85
Matthew Skelton, Conflux
@matthewpskelton
Manuel Pais, Independent
@manupaisable
Copyright © Conflux Digital Ltd 2018-2019. All rights reserved.
Registered in England and Wales, number 10890964
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